法医学杂志

法医学杂志 ›› 2020, Vol. 36 ›› Issue (1): 91-98.DOI: 10.12116/j.issn.1004-5619.2020.01.018

• 综述 • 上一篇    下一篇

机器学习在骨龄评估中的研究进展及展望

彭丽琴1， 万雷2， 汪茂文2， 李卓2， 赵虎1， 王亚辉2   

  1. 1. 中山大学中山医学院法医学系，广东 广州 510080； 2. 司法鉴定科学研究院 上海市法医学重点实验室 司法部司法鉴定重点实验室 上海市司法鉴定专业技术服务平台，上海 200063
  • 发布日期:2020-02-25 出版日期:2020-02-28
  • 通讯作者: 赵虎，男，博士，教授，博士研究生导师，主要从事法医精神病学与法医临床学研究；E-mail：zhaohu3@mail.sysu.edu.cn 王亚辉，男，副研究员，主要从事法医临床学、法医人类学研究；E-mail：wangyh@ssfjd.cn
  • 作者简介:彭丽琴（1995—），女，土家族，硕士研究生，主要从事法医临床学研究；E-mail：pengliqinmn@163.com
  • 基金资助:
    国家自然科学面上基金资助项目（81571859，81273350，81471829）；上海市法医学重点实验室资助项目（17DZ2273200）；上海市司法鉴定专业技术服务平台资助项目（19DZ2292700）；上海市法医学重点实验室开放基金资助项目（KF1706）

Research Progress and Prospect of Machine Learning in Bone Age Assessment

PENG Li-qin1, WAN Lei2, WANG Mao-wen2, LI Zhuo2, ZHAO Hu1, WANG Ya-hui2   

  1. 1. Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun-Yat Sen University, Guangzhou 510080, China; 2. Shanghai Key Laboratory of Forensic Medicine, Key Laboratory of Forensic Science, Ministry of Justice, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, China
  • Online:2020-02-25 Published:2020-02-28

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摘要： 骨龄评估一直是法医学研究领域的重点及难点问题之一。近年来，随着机器学习在诸多行业内的逐渐兴起，其已被广泛引入影像学、基因组学、肿瘤学、病理学以及外科学等医学研究领域中。上述研究领域之所以能与机器学习紧密结合，主要是由于上述医学分支学科中的研究对象属于计算机视觉范畴，而机器学习对于计算机视觉研究有着得天独厚的优势，并在医学图像识别中取得突破性进展。基于机器学习在图像识别中的优势，将其与骨龄评估研究有机结合，旨在为构建适用于法医学骨骼影像图片的识别模型。基于此，本文将对近年来国内外学者运用机器学习技术在骨龄评估中的研究进展进行综述。

关键词: 法医人类学；年龄测定, 骨骼；机器学习；综述

Abstract: Bone age assessment has always been one of the key issues and difficulties in forensic science. With the gradual development of machine learning in many industries, it has been widely introduced to imageology, genomics, oncology, pathology, surgery and other medical research fields in recent years. The reason why the above research fields can be closely combined with machine learning, is because the research subjects of the above branches of medicine belong to the computer vision category. Machine learning provides unique advantages for computer vision research and has made breakthroughs in medical image recognition. Based on the advantages of machine learning in image recognition, it was combined with bone age assessment research, in order to construct a recognition model suitable for forensic skeletal images. This paper reviews the research progress in bone age assessment made by scholars at home and abroad using machine learning technology in recent years.

Key words: forensic anthropology, age determination by skeleton, machine learning, review